Method of multi-spectral images reduce-dimensions based on PCA

Image processing has been widely used in different fields in our daily life,compared to other images,hyper-extraction images is bigger,with more data and contains more information,which made it difficult to analysis.So before the classification process,reduce image dimensions made it easier,faster,with less space to classify.This article has improved the mentioned a kind of image dimension-reducing methods,for the multi-spectral images,it uses the traditional PCA transformation first,the matrix transform to reduce the relations between each images,and also reduces a little noises.Since it considers little about noises,after the PCA transformation,uses low-pass filters to remove the noises in the images.This improved the classification accuracy.